This might be a naive question but I am unable to understand how to use metric MDS. When following the examples in the documentation, I only get classical MDS out. In the documentation, an example for classical MDS (cMDS) is provided, using the code
using MultivariateStats
# ... prepare data X ...
M = fit(MDS, X; maxoutdim=3, distances=false)
# returns "Classical MDS(indim = 4, outdim = 3)"
However, no example for metric MDS (mMDS) is given. Scrolling down, there are 2 sections, one explaining cMDS and one mMDS. In the mMDS section, the code provided to call mMDS seems to be the same as for cMDS:
mds = fit(MDS, X; distances=false, maxoutdim=size(X,1)-1)
There is no specification what one has to load before that to make the function return an mMDS object instead of a cMDS object. (Maybe this is also related to me lacking general knowledge of julia?) I tried things like
using MultivariateStats.MetricMDS
mds = fit(MDS, X; distances=false, maxoutdim=size(X,1)-1)
or
using MultivariateStats
mds = fit(MetricMDS, X; distances=false, maxoutdim=size(X,1)-1)
or
using MultivariateStats
mds = fit(MDS::MetricMDS, X; distances=false, maxoutdim=size(X,1)-1)
but all return errors. Is there a problem with the documentation or am I just doing a silly mistake? Thanks a lot!
This might be a naive question but I am unable to understand how to use metric MDS. When following the examples in the documentation, I only get classical MDS out. In the documentation, an example for classical MDS (cMDS) is provided, using the code
However, no example for metric MDS (mMDS) is given. Scrolling down, there are 2 sections, one explaining cMDS and one mMDS. In the mMDS section, the code provided to call mMDS seems to be the same as for cMDS:
There is no specification what one has to load before that to make the function return an mMDS object instead of a cMDS object. (Maybe this is also related to me lacking general knowledge of julia?) I tried things like
or
or
but all return errors. Is there a problem with the documentation or am I just doing a silly mistake? Thanks a lot!